code: def get_stlarima_nemo_pipeline():
      """ Function return complex pipeline with the following structure
          stl_arima \
                     linear
              nemo  |
      """
  
      node_arima = PipelineNode("stl_arima")
      node_arima.parameters = {"period": 80, "p": 2, "d": 1, "q": 0}
      node_nemo = PipelineNode("exog_ts")
      node_final = PipelineNode(
          "linear", nodes_from=[node_arima, node_nemo]
      )
      pipeline = Pipeline(node_final)
      return pipeline
  
imports: import os
  from copy import deepcopy
  import numpy
  import pandas
  from matplotlib import pyplot
  from sklearn.metrics import mean_squared_error, mean_absolute_error
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TsForecastingParams, TaskTypesEnum
label_desc: Use image node_id 4 for calling a global function with example usage: get_stlarima_nemo_pipeline() and returns: pipeline